Seminar Description: Artificial Intelligence (AI), machine learning (ML), and deep learning (DL) are transforming the way we work, live, and interact with each other. The emergence of these cognitive technologies are transforming the way public sector agencies and citizens
interact with each other. But putting AI, ML, and DL into practice and getting beyond the buzzwords is a challenge. This seminar focuses on providing attendees with a current state of the ML and DL markets, and will discuss the state of the practice
with real use cases and methodologies to make AI projects a tangible success for public and private sector organizations.

Attendees will learn:

How to dispel popular myths about intelligent automation and learning systems

About your AI options, who are the players, and what are the key technologies

From world-class machine learning experts who are developing innovative public sector applications today

Insights into what makes AI projects a success across a wide range of agencies

A roadmap for successful AI adoption within their agency or enterprise, and

While artificial intelligence has been around for decades, it’s only recently that machine learning, deep learning, and other cognitive technologies are at the point where they can be practically realized by organizations. This session sets the
bar for what AI represents today and provides definitions and level-setting of terminology. We bust some myths about AI, point to real-world applications of AI in large scale implementations, and explore how AI will impact our future illustrating
what an AI-enabled future will look like.

The key takeaway of this seminar is a self-assessment for an AI Project Fit. Attendees will learn:

Organizations of all types want to incorporate AI, machine learning, and cognitive technologies into their operations and processes to augment human workers, increase efficiencies, reduce costs, and achieve the goals of more intelligent systems. But,
figuring out how to successfully run an AI project can be daunting. This session will help attendees learn how to successfully identify key problem areas that AI technologies can address, the six primary adoption patterns for AI and cognitive technologies
with use cases for each pattern, as well as iterative approaches to AI implementation. At the end of the session, attendees will leave with an AI Implementation Roadmap to help successfully start and complete your adoption of AI projects.

The key takeaway of this session is to provide you with a self-assessment of your AI implementation roadmap. Attendees will learn:

Bots aren’t just physical - they can be software as well. AI-powered software bots are doing everything from tedious entry of data to more sophisticated multi-step processes that have previously required significant human labor. In this panel discussion,
we hear the insights of several leaders in the emerging intelligent automation and cognitive automation space and hear first-hand how AI and machine learning are being applied to complex processes. Learn about Robotic Process Automation (RPA) solutions,
intelligent automation offerings, and emerging cognitive automation approaches, and how agencies and organizations of all types are using software bots to help automate various processes and tasks.

The vendor landscape for AI and machine learning technologies is getting very crowded with thousands of companies offering solutions, and new vendors emerging monthly. However, these vendors are offering a confusing array of solutions that can be a challenge
to understand for organizations looking to implement AI projects. In this session, we explore a rational classification system for AI vendors, how to evaluate AI vendors to meet the needs of various AI projects, and understand how the landscape is
developing over time.This session will present:

A comprehensive classification of the AI vendor ecosystem

The various infrastructural considerations for AI projects

A proven process to help you choose the right vendor(s) for your project(s)

Organizations and agencies are looking to put AI into practice, but the main challenge is that AI projects are not like typical application development projects. In this session, we will discuss best practices and approaches to manage AI projects, the
data-centric nature of AI solutions, and the specific requirements for particular AI implementation patterns. We will present a methodology that combines the best of Agile and CRISP-DM approaches, pitfalls to watch out for with AI adoption while addressing
governance, transparency, and ethics concerns, and how to deal with emerging AI threats.Attendees will learn an Agile/CRISP-DM methodology adapted for AI, including discussions on:

Data-centric vs. application-centric AI approaches

Learning from others: examples of AI projects at scale

How to provide governance & transparency around AI, and how to establish an AI ethics process- Healthcare needs (HIPAA, data protection/privacy and security)

What are the pitfalls in AI adoption?- There is what’s known as the “Golden data” on threats available to train against- Dealing with AI threats

Seminar Closing Remarks

Ronald Schmelzer, Managing Partner, Principal Analyst, Cognilytica

Led by

Monday, June 24 | 1:30 – 5:00 pm

Seminar: AI & Cybersecurity

Chair: Bob Gourley, Co-Founder and CTO, OODA LLC

Seminar Description: Cybersecurity is a major area of interest in today’s internet, and while the threats are no longer as widely discussed as they used to be, they are arguably more dangerous than ever. How can machine learning help with malware research? The
state of the practice and state of technology of AI in cybersecurity will be addressed.

Seminar Introduction: When AI goes Wrong

Bob Gourley, Co-Founder and CTO, OODA LLC

AI for National Security Missions

Jason Matheny, PhD, Founding Director of the Center for Security and Emerging Technology, Georgetown University

To detect a trusted individual who might do malicious things with authorized credentials has been classified as one of the toughest and most costly cybersecurity problems. Even accidental incidents generate average damages of millions per year for small
organizations. This talk will demonstrate some machine learning approaches to solve classically challenging insider threats, including re-discovering Enron fraud instances from email only and finding leakers or saboteurs before they act.

Seminar: Conversational Interfaces - State of the Practice of Intelligent Assistants

Chair: William Meisel, PhD, President, TMA Associates

Seminar Description: Speech recognition and natural
language processing technology allows interacting with digital systems using human language in text or speech. An organization can use the technology to improve customer service, not only in the call center, but through chatbots on web sites,
apps on mobile phones, messaging services, home speakers, through the major personal assistants, and more. The technology can also make personnel more effective within organizations in tasks such as using software systems or on-the-job training.
This seminar discusses innovative applications deployed by agencies and the tools available to help develop conversational solutions and practices that make those solutions effective.

The State of the Practice in Intelligent Assistants

William Meisel, PhD, President, TMA Associates

The AI technology behind talking and texting with computer applications using human language (“natural language
understanding”) has matured. Amazon's Alexa and Google Assistant exemplify the advanced use of this technology, but companies are increasingly using more limited versions to help both customers and employees.

This session will present the state of the technology, how some companies are taking advantage of it, and tools that help deploy company-specific intelligent assistants without a research project. Topics covered include:

The state of speech recognition and natural language processing technology

Using intelligent assistants in marketing and sales

Examples of deployed digital assistants and their effectiveness

Available tools for building customer service chatbots and automated assistants

Available tools for building employee support applications ("Augmented Intelligence")

In this talk, the benefits of conversational self-service for several government agencies over the last 13 years are highlighted, as well as the positive effect that anonymous communication with autonomous agents can have on users. By providing conversational
self-service options, users can find answers to sensitive questions without fear of judgment and agencies can collect more holistic feedback on what users really want to know from them.